The application of the differential evolution method in two important areas of applied electromagnetics is discussed in this chapter. The first one refers to the synthesis and design of array antennas, for which differential evolution, as well as other evolutionary algorithms, is now considered a fundamental design tool. The second one concerns the diagnostic applications faced as a result of using radiofrequency and microwave imaging techniques. Being based on the inverse scattering problem, these techniques suffer from nonlinearity and ill posedness. The differential evolution method has been successfully proposed for optimizing this multimodal and complex inverse problem. The chapter includes a brief review of some results recently publi...
[[abstract]]The inverse problem under consideration is to reconstruct the characteristic of scattere...
In this paper, a hybrid differential evolution and weight total least squares method (HDE-WTLSM) is ...
10.1109/CEC.2007.44250332007 IEEE Congress on Evolutionary Computation, CEC 20074305-431
The application of the differential evolution method in two important areas of applied electromagnet...
This paper presents an efficient and reliable inversion methodology for microwave imaging based on a...
Electromagnetic inverse scattering problems arise in several diagnostic applications, in which the o...
[[abstract]]The application of four techniques for the shape reconstruction of a metallic cylinder b...
Abstract: The differential evolution (DE) algorithm with a new differential mutation base strategy, ...
Recently, evolutionary algorithms (e.g. genetic algorithms, evolutionary programming, and evolution ...
A review of evolutionary algorithms (EAs) with applications to antenna and propagation problems is p...
A review of evolutionary algorithms (EAs) with applications to antenna and propagation problems is p...
Abstract—In this article, a novel numerical technique, called Fitness Adaptive Differential Evolutio...
The differential evolution (DE) algorithm with a newdifferential mutation base strategy, namely best...
A review of evolutionary algorithms (EAs) with applications to antenna and propagation problems is p...
Several evolutionary algorithms (EAs) have emerged in the past decades that mimic biological entitie...
[[abstract]]The inverse problem under consideration is to reconstruct the characteristic of scattere...
In this paper, a hybrid differential evolution and weight total least squares method (HDE-WTLSM) is ...
10.1109/CEC.2007.44250332007 IEEE Congress on Evolutionary Computation, CEC 20074305-431
The application of the differential evolution method in two important areas of applied electromagnet...
This paper presents an efficient and reliable inversion methodology for microwave imaging based on a...
Electromagnetic inverse scattering problems arise in several diagnostic applications, in which the o...
[[abstract]]The application of four techniques for the shape reconstruction of a metallic cylinder b...
Abstract: The differential evolution (DE) algorithm with a new differential mutation base strategy, ...
Recently, evolutionary algorithms (e.g. genetic algorithms, evolutionary programming, and evolution ...
A review of evolutionary algorithms (EAs) with applications to antenna and propagation problems is p...
A review of evolutionary algorithms (EAs) with applications to antenna and propagation problems is p...
Abstract—In this article, a novel numerical technique, called Fitness Adaptive Differential Evolutio...
The differential evolution (DE) algorithm with a newdifferential mutation base strategy, namely best...
A review of evolutionary algorithms (EAs) with applications to antenna and propagation problems is p...
Several evolutionary algorithms (EAs) have emerged in the past decades that mimic biological entitie...
[[abstract]]The inverse problem under consideration is to reconstruct the characteristic of scattere...
In this paper, a hybrid differential evolution and weight total least squares method (HDE-WTLSM) is ...
10.1109/CEC.2007.44250332007 IEEE Congress on Evolutionary Computation, CEC 20074305-431